1. The point estimator for the
1. The point estimator for the population standard deviation σ is ___ and the point estimator for the population mean μ is ____.
2. To estimate the value of a population parameter using a sample, we would calculate…
a) a simple random sample, b) a sample statistic, c) a test statistic, d) or both a and b
3. A simple random sample from a finite data set must meet which condition(s)/requirements?
a) you may only sample without replacement; sampling with replacement eliminates the randomness of the sample.
b) each sample selected should include at least 1 observation forma previous sample
c) each sample ( of size n selected from a finite population of size N) should have the same probability of being selected
d) none of the above
4. if the population with which you are working is not normally distributed…
a) you cannot assume the sampling distribution is normally distributed under any circumstances
b) you can assume the sampling distribution is normally distributed if the condition of the Central Limit Theorem is met
c) you can assume the sampling distribution is normally distributed but not by the means described above.
Answer:
(1)
The point estimator for the population standard deviation
isSample StandardDeviation s and point estimator for the population mean
is Sample Mean
.
Explanation:By definition, a sample statistic is thecharacteristic of a sample is a point estimator of populationparameter, which is the characteristic of the population. Thesample standard deviation (s) is a point estimate of the populationstandard deviation (). The samplemean () is a pointestimate of the population mean ()
(2)
Correct option:
(b) a samplestatistic
Explanation: To estimate the population parameter, we firstcalculate the corresponding sample statistic from the availablesample data.
(3)
Correct option:
(c) Each sample (of size n selected from a finitepopulation of size N) should have the same probability of beingselected.
Explanation: By definition, a Simple Random Sample (SRS) fromfinite population of size N is a random sample selected by a methodwhich ensures that all possible samples, of given size n, areequally likely to be chosen.
(4)
Correct option:
(b) you can assumethe sampling distribution is normally distributed if the conditionsof the Central Limit Theorem is met.
Explanation: By Central Limit Theorem, the sampling distributionof a sample statistic is Normal Distribution irrespective of theshape of the population for large samples,i.e., n > 30.
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